using 
CSV,
Dates,
DataFrames,
Markdown,
Plots,
Statistics,
StatsPlots
gr()
;

death_path = "COVID-19/csse_covid_19_data/csse_covid_19_time_series/time_series_covid19_deaths_global.csv"
confirmed_path = "COVID-19/csse_covid_19_data/csse_covid_19_time_series/time_series_covid19_confirmed_global.csv"
;

death = CSV.read(death_path) |> DataFrame! |> x -> rename!(x, Dict(Symbol("Province/State") => :state, Symbol("Country/Region") => :country))
confirmed = CSV.read(confirmed_path) |> DataFrame! |> x -> rename!(x, Dict(Symbol("Province/State") => :state, Symbol("Country/Region") => :country))
;

"""
    convert an array of columns and column names into a markdown table

    parameters: 
        cols : Array[Array[Any]] | DataFrame
            an array of arrays which are the columns of the table
        names : Array[String]
            an array of column names. If inputting a df, input `string.(names(df))`
        df : Boolean
            whether or not the cols are an array of arrays or a dataframe

    returns: String
        string of markdown text
"""
function markdown_table(cols, names; df=false)
    if df
        cols = [col for col in eachcol(cols)]
    end
    output_string = ""
    cols = [repr.(col) for col in cols]
    for i in 1:length(names)
        output_string = output_string * "|" * names[i]
    end
    output_string *= "\n"
    for i in 1:length(names)
        output_string = output_string * "|" * "---"
    end
    output_string *= "\n"
    for row in 1:length(cols[1])
        for col in 1:length(cols)
            output_string = output_string * "|" * cols[col][row]
        end
        output_string *= "\n"
    end
    # displaying strings without quotes
    output_string =  replace(output_string, "\"" => "")

    return output_string
end
;

function country_data(country; state=false, start_date=Dates.Date(2020, 1, 22), end_date="max")
    aggregate(x) = [sum(col) for col in eachcol(x)]
    
    state_mask = typeof(state) == String ? death.state .== state : true
    d = death[(death.country .== country) .& state_mask, 5:end] |> aggregate
    dates = [Dates.Date(2020, 1, 22) + Dates.Day(day) for day in 1:length(d)] |> x -> reshape(x, :, 1)
    state_mask = typeof(state) == String ? confirmed.state .== state : true
    c = confirmed[(confirmed.country .== country) .& state_mask, 5:end] |> aggregate
    
    df = convert(DataFrame, dates) |> x -> rename!(x, [:date])
    country_name = typeof(state) == String ? country * "-" * state : country
    df[!, :country] .= country_name
    df[!, :confirmed] = c
    df[!, :deaths] = d
    df[!, :death_rate] = d ./ c
    df[!, :new_cases] .= 0
    df[2:end, :new_cases] = df[2:end, :confirmed] .- df[1:end-1, :confirmed]
    df[!, :new_deaths] .= 0
    df[2:end, :new_deaths] = df[2:end, :deaths] .- df[1:end-1, :deaths]
    df[!, :acceleration_cases] .= 0
    df[2:end, :acceleration_cases] = df[2:end, :new_cases] .- df[1:end-1, :new_cases]
    df[!, :acceleration_deaths] .= 0
    df[2:end, :acceleration_deaths] = df[2:end, :new_deaths] .- df[1:end-1, :new_deaths]
    df[!, :days_since_100] .= 0
    counter = 0
    for row in eachrow(df)
        if row.confirmed > 100
            counter += 1
        end
        row.days_since_100 = counter
    end
    df[!, :days_since_10] .= 0
    counter = 0
    for row in eachrow(df)
        if row.deaths > 10
            counter += 1
        end
        row.days_since_10 = counter
    end
    
    if end_date == "max"
        end_date = maximum(df.date)
    end
    return df[(df.date .>= start_date) .& (df.date .<= end_date), :]
end
;

function plot_country(country; state=false, metric=:confirmed, start_date=Dates.Date(2020, 1, 22), end_date="max", days_since_100=false)
    data = country_data(country; state=state, start_date=start_date, end_date=end_date)
    if days_since_100
        if metric == :confirmed
            plot(data[data.days_since_100 .> 0, :days_since_100], data[data.days_since_100 .> 0, metric], label=country, legend=:outertopright, size=(1000, 500))
        else
            plot(data[data.days_since_10 .> 0, :days_since_10], data[data.days_since_10 .> 0, metric], label=country, legend=:outertopright, size=(1000, 500))
        end
    else
        plot(data.date, data[!, metric], label=country, legend=:outertopright, size=(1000, 500))
    end
    
    plot!([0], linetype=:hline, color=:black, label="")
    plot!(yformatter=:plain)
end
function plot_country!(country; state=false, metric=:confirmed, start_date=Dates.Date(2020, 1, 22), end_date="max", days_since_100=false)
    data = country_data(country; state=state, start_date=start_date, end_date=end_date)
    if days_since_100
        if metric == :confirmed
            plot!(data[data.days_since_100 .> 0, :days_since_100], data[data.days_since_100 .> 0, metric], label=country, legend=:outertopright, size=(1000, 500))
        else
            plot!(data[data.days_since_10 .> 0, :days_since_10], data[data.days_since_10 .> 0, metric], label=country, legend=:outertopright, size=(1000, 500))
        end
    else
        plot!(data.date, data[!, metric], label=country, legend=:outertopright, size=(1000, 500))
    end
    plot!(yformatter=:plain)
end
bar_plot(country, metric) = bar(
    all_country_data[
        (all_country_data.country .== country) .& (all_country_data.date .>= Dates.Date(2020, 1, 1)),
        :date
    ], 
    all_country_data[
        (all_country_data.country .== country) .& (all_country_data.date .>= Dates.Date(2020, 1, 1)),
        metric
    ], 
    legend=false, 
    linecolor=1, 
    title=country,
    yformatter=:plain
)
function accel_plot(country_name="World")
    if country_name == "World"
        tmp = all_country_data
    else
        tmp = all_country_data[all_country_data.country .== country_name, :]
    end
    agg = by(tmp, [:date], :confirmed => sum, :deaths => sum)
    conf = plot(agg.date, agg.confirmed_sum, legend=false, title="$country_name Confirmed Cases", size=(1400, 700), color=:grey, yformatter=:plain)
    death_plot = plot(agg.date, agg.deaths_sum, legend=false, title="$country_name Deaths", size=(1400, 700), color=:orange, yformatter=:plain)

    # derivates
    agg[!, :new_cases] .= 0
    agg[!, :new_cases][2:end] = agg.confirmed_sum[2:end] - agg.confirmed_sum[1:end-1]
    agg[!, :new_deaths] .= 0
    agg[!, :new_deaths][2:end] = agg.deaths_sum[2:end] - agg.deaths_sum[1:end-1]
    agg[!, :conf_acceleration] .= 0
    agg[!, :conf_acceleration][2:end] = agg.new_cases[2:end] - agg.new_cases[1:end-1]
    agg[!, :death_acceleration] .= 0
    agg[!, :death_acceleration][2:end] = agg.new_deaths[2:end] - agg.new_deaths[1:end-1]

    # moving average
    moving_average(vs,n) = [sum(@view vs[i:(i+n-1)])/n for i in 1:(length(vs)-(n-1))]
    n_days = 3
    ma_date = agg.date[1 + n_days-1:end]
    conf_slope = moving_average(agg.new_cases, n_days)
    death_slope = moving_average(agg.new_deaths, n_days)
    conf_acc = moving_average(agg.conf_acceleration, n_days)
    death_acc = moving_average(agg.death_acceleration, n_days)

    p_conf_slope = plot(ma_date, conf_slope, legend=false, title="$country_name 1st Derivative (new cases)", size=(1400, 700), color=:grey)
    plot!([0], linetype=:hline, color=:black, label="", yformatter=:plain)

    p_death_slope = plot(ma_date, death_slope, legend=false, title="$country_name 1st Derivative (new deaths)", size=(1400, 700), color=:orange)
    plot!([0], linetype=:hline, color=:black, label="", yformatter=:plain)

    p_conf_acc = plot(ma_date, conf_acc, legend=false, title="$country_name 2nd Derivative (cases acceleration)", size=(1400, 700), color=:grey)
    plot!([0], linetype=:hline, color=:black, label="", yformatter=:plain)

    p_death_acc = plot(ma_date, death_acc, legend=false, title="$country_name 2nd Derivative (deaths acceleration)", size=(1400, 700), color=:orange)
    plot!([0], linetype=:hline, color=:black, label="", yformatter=:plain)

    plot(conf, death_plot, p_conf_slope, p_death_slope, p_conf_acc, p_death_acc, layout=(3,2))
end
;

all_countries = death.country |> unique |> sort
all_country_data = vcat([country_data(country) for country in all_countries]...)
current_state = by(all_country_data, [:country], :confirmed => maximum, :deaths => maximum)
current_state[!, :death_rate] = current_state.deaths_maximum ./ current_state.confirmed_maximum
;

Markdown.parse("""
    # Overview of COVID-19 as of $(maximum(all_country_data.date))
    This page uses data from https://github.com/CSSEGISandData/COVID-19 (Johns Hopkins CSSE is the original source) to create a report on the status of COVID-19 cases and deaths around the world. It is updated once a day around 10:00am CET.
    """)

Worldwide Current State¶

tmp = current_state
Markdown.parse("""
- Confirmed cases: $(sum(tmp.confirmed_maximum))
- Deaths: $(sum(tmp.deaths_maximum))
- Death Rate: $(round(sum(tmp.deaths_maximum) / sum(tmp.confirmed_maximum) * 100, digits=2))%
""")

accel_plot("World")
plot!(size=(900, 700))

Top 10 Worst Affected Countries¶

Confirmed¶

top_10 = sort(current_state, order(:confirmed_maximum, rev=true))[1:10, :]
top_10[!, :death_rate] = string.(round.(top_10.death_rate * 100, digits=2)) .* "%"
Markdown.parse(
    markdown_table(top_10, ["Country", "Confirmed Cases", "Deaths", "Death Rate"]; df=true)
)

Acceleration (>1000 cases now)¶

The Acceleration of Last 5 Days column is calculated by the average second derivative over the last 5 days / number of cases 5 days ago. It doesn't have much intrinsic meaning but is rather a more comparable/relative measure between countries of how fast new cases are accelerating.

countries = unique(all_country_data.country)
acceleration = []
cases_5_ago = []
cases_now = []
for country in countries
    metric = mean(all_country_data[all_country_data.country .== country, :acceleration_cases][end-4:end])
    metric /= all_country_data[all_country_data.country .== country, :confirmed][end-4]
    if isnan(metric)
        metric = 0
    end
    push!(acceleration, metric)
    push!(cases_5_ago, all_country_data[all_country_data.country .== country, :confirmed][end-4])
    push!(cases_now, all_country_data[all_country_data.country .== country, :confirmed][end])
end
last_5 = rename!(DataFrame([countries, acceleration, cases_now, cases_5_ago]), [:country, :last_5_accel, :cases_now, :cases_5_ago])
last_5[!, :perc_increase] = last_5.cases_now ./ last_5.cases_5_ago .- 1
tmp = sort(last_5[(last_5.cases_5_ago .> 20) .& (last_5.cases_now .> 1000), :], order(:last_5_accel, rev=true))
tmp[!, :perc_increase] = string.(round.(tmp.perc_increase .* 100, digits=2)) .* "%"
rename!(tmp, [:Country, Symbol("Acceleration of Last 5 Days"), Symbol("Cases Now"), Symbol("Cases 5 Days Ago"), Symbol("% Increase in 5 Days")])
tmp[!, Symbol("Acceleration of Last 5 Days")] = string.(round.(tmp[!, Symbol("Acceleration of Last 5 Days")] * 100, digits=2)) .* "%"

Markdown.parse(
    markdown_table(tmp, string.(names(tmp)), df=true)
)

function individual_country(country; comparison_country="Italy")
    # line plots
    cases_100 = plot_country(country, days_since_100=true, metric=:confirmed)
    plot_country!(comparison_country, days_since_100=true, metric=:confirmed)
    plot!(title="$country Days Since 100th Case", titlefont=font(10))
    deaths_10 = plot_country(country, days_since_100=true, metric=:deaths)
    plot_country!(comparison_country, days_since_100=true, metric=:deaths)
    plot!(title="$country Days Since 10th Death", titlefont=font(10))
    line_plots = plot(cases_100, deaths_10, layout=(2,1))
    
    #accel plots
    accel_plots = accel_plot(country)
    plot!(titlefont=font(10))
    
    # bar plots
    cases_bar = bar_plot(country, :new_cases)
    plot!(title="$country New Cases Per Day", titlefont=font(10))
    deaths_bar = bar_plot(country, :new_deaths)
    plot!(title="$country Deaths Per Day", titlefont=font(10))
    bar_plots = plot(cases_bar, deaths_bar, layout=(2,1))
    
    final_plot = plot(accel_plots, line_plots, bar_plots, layout=(3, 1))
    plot!(size=(900, 1400))
    return final_plot
end
;

Countries¶

Days since 100th case and 10th death plotted with Italy for comparison. Only countries with >= 500 confirmed cases show graphs. Derivative plots are 3 days moving average.

for coun in all_countries
    data = country_data(coun)
    display(Markdown.parse("## $coun"))
    Markdown.parse("""
- Confirmed cases: $(maximum(data.confirmed))
- Deaths: $(maximum(data.deaths))
- Death Rate: $(round(maximum(data.deaths) / maximum(data.confirmed) * 100, digits=2))%
""") |> display
    if maximum(data.confirmed) >= 500 || coun == "Hungary"
        display(individual_country(coun))
    end
end

Country	Confirmed Cases	Deaths	Death Rate
US	161807	2978	1.84%
Italy	101739	11591	11.39%
Spain	87956	7716	8.77%
China	82198	3308	4.02%
Germany	66885	645	0.96%
France	45170	3030	6.71%
Iran	41495	2757	6.64%
United Kingdom	22453	1411	6.28%
Switzerland	15922	359	2.25%
Belgium	11899	513	4.31%

Country	Acceleration of Last 5 Days	Cases Now	Cases 5 Days Ago	% Increase in 5 Days
Turkey	5.78%	10827	3629	198.35%
Romania	3.54%	2109	1029	104.96%
Russia	3.31%	1836	840	118.57%
Canada	3.25%	7398	4042	83.03%
India	2.92%	1251	727	72.08%
US	2.12%	161807	83836	93.0%
United Kingdom	2.03%	22453	11812	90.09%
Austria	1.52%	9618	6909	39.21%
Chile	1.38%	2449	1306	87.52%
Belgium	1.27%	11899	6235	90.84%
Philippines	1.24%	1546	707	118.67%
France	1.0%	45170	29551	52.85%
Poland	0.7%	2055	1221	68.3%
Iran	0.67%	41495	29406	41.11%
Ireland	0.66%	2910	1819	59.98%
Sweden	0.62%	4028	2840	41.83%
Indonesia	0.56%	1414	893	58.34%
Thailand	0.56%	1524	1045	45.84%
Finland	0.5%	1352	958	41.13%
Pakistan	0.48%	1717	1201	42.96%
Denmark	0.46%	2755	2023	36.18%
Saudi Arabia	0.42%	1453	1012	43.58%
Australia	0.41%	4361	2810	55.2%
Germany	0.21%	66885	43938	52.23%
Switzerland	0.12%	15922	11811	34.81%
Brazil	0.11%	4579	2985	53.4%
Netherlands	0.08%	11817	7468	58.24%
China	0.0%	82198	81782	0.51%
Korea, South	-0.05%	9661	9241	4.54%
Malaysia	-0.16%	2626	2031	29.3%
Italy	-0.29%	101739	80589	26.24%
Norway	-0.36%	4445	3369	31.94%
Greece	-0.49%	1212	892	35.87%
Iceland	-0.57%	1086	802	35.41%
Spain	-0.62%	87956	57786	52.21%
Ecuador	-0.76%	1962	1403	39.84%
Czechia	-0.79%	3001	1925	55.9%
Portugal	-1.06%	6408	3544	80.81%
Japan	-1.64%	1866	1387	34.53%
South Africa	-2.35%	1326	927	43.04%
Luxembourg	-2.7%	1988	1453	36.82%
Israel	-5.07%	4695	2693	74.34%

Overview of COVID-19 as of 2020-03-31¶

Worldwide Current State¶

Top 10 Worst Affected Countries¶

Confirmed¶

Acceleration (>1000 cases now)¶

Countries¶

Afghanistan¶

Albania¶

Algeria¶

Andorra¶

Angola¶

Antigua and Barbuda¶

Argentina¶

Armenia¶

Australia¶

Austria¶

Azerbaijan¶

Bahamas¶

Bahrain¶

Bangladesh¶

Barbados¶

Belarus¶

Belgium¶

Belize¶

Benin¶

Bhutan¶

Bolivia¶

Bosnia and Herzegovina¶

Botswana¶

Brazil¶

Brunei¶

Bulgaria¶

Burkina Faso¶

Burma¶

Cabo Verde¶

Cambodia¶

Cameroon¶

Canada¶

Central African Republic¶

Chad¶

Chile¶

China¶

Colombia¶

Congo (Brazzaville)¶

Congo (Kinshasa)¶

Costa Rica¶

Cote d'Ivoire¶

Croatia¶

Cuba¶

Cyprus¶

Czechia¶

Denmark¶

Diamond Princess¶

Djibouti¶

Dominica¶

Dominican Republic¶

Ecuador¶

Egypt¶

El Salvador¶

Equatorial Guinea¶

Eritrea¶

Estonia¶

Eswatini¶

Ethiopia¶

Fiji¶

Finland¶

France¶

Gabon¶

Gambia¶

Georgia¶

Germany¶

Ghana¶

Greece¶

Grenada¶

Guatemala¶

Guinea¶

Guinea-Bissau¶

Guyana¶

Haiti¶

Holy See¶